Building Word Representations for Wolof Using Neural Networks

Because a large portion of population in rural areas in sub Saharan Africa understand only local languages, they do not have access all to content available in the World Wide Web. Most content are available in English, Spanish, French, etc. Content in low-resource languages such as Wolof, which is mostly spoken in Senegal, are scarce. Automatic systems for natural language understanding such as machine translation systems that can transform information from common to low-resource languages would allow people in rural areas to access relevant scientific or health content.